Difference between revisions of "2010 Summer Project Week Best Regularization Term for Demons Registration Algorithm"
(Created page with '__NOTOC__ <gallery> Image:PW-MIT2010.png|Projects List </gallery> ==Key Investigators== * MGH: Rui Li, Greg Sharp <div style="margin: 20px…') |
|||
(6 intermediate revisions by the same user not shown) | |||
Line 19: | Line 19: | ||
<h3>Approach, Plan</h3> | <h3>Approach, Plan</h3> | ||
− | + | Our plan is to find a way to convert the current research code into an itk module that can | |
+ | be loaded into slicer. | ||
</div> | </div> | ||
Line 26: | Line 27: | ||
<h3>Progress</h3> | <h3>Progress</h3> | ||
− | + | ||
+ | The research code is a mixture of MATLAB and C code. Thanks to the discussion with Luis, we have | ||
+ | successfully implemented itkCurvatureDemonsFilter.* and itkCurvatureDemonsFunction.* for a variant of | ||
+ | the Demons algorithm with the curvature regularization term. | ||
+ | |||
+ | Our next steps after this project week are: (1). implement locally adaptive curvature based Demons algorithm. | ||
+ | (2). implement Demons algorithm that uses L1-regularization term, this step will take more time and effort. | ||
+ | itkPDEDeformableRegistrationFilter.* and itkPDEDeformableRegistrationFunction.* need to be rewritten. | ||
+ | |||
</div> | </div> | ||
Line 34: | Line 43: | ||
==Delivery Mechanism== | ==Delivery Mechanism== | ||
− | + | All the implementations will be included into plastimatch. | |
− | |||
==References== | ==References== | ||
− | + | * ''Demons algorithms for fluid and curvature registration''. Cahill, N.D., Noble, J.A., Hawkes, D.J. ISBI 2009. | |
+ | * ''A Demons Algorithm for Image Registration with Locally Adaptive Regularization''. Cahill, N.D., Noble, J.A., Hawkes, D.J.. MICCAI 2009. | ||
+ | * ''High Accuracy Optical Flow Estimation Based on a Theory for Warping''. Brox, T. et al., ECCV 2004 | ||
</div> | </div> |
Latest revision as of 03:31, 25 June 2010
Home < 2010 Summer Project Week Best Regularization Term for Demons Registration AlgorithmKey Investigators
- MGH: Rui Li, Greg Sharp
Objective
- Show comparison of the demons algorithm performance with different regularization terms.
Approach, Plan
Our plan is to find a way to convert the current research code into an itk module that can be loaded into slicer.
Progress
The research code is a mixture of MATLAB and C code. Thanks to the discussion with Luis, we have successfully implemented itkCurvatureDemonsFilter.* and itkCurvatureDemonsFunction.* for a variant of the Demons algorithm with the curvature regularization term.
Our next steps after this project week are: (1). implement locally adaptive curvature based Demons algorithm. (2). implement Demons algorithm that uses L1-regularization term, this step will take more time and effort. itkPDEDeformableRegistrationFilter.* and itkPDEDeformableRegistrationFunction.* need to be rewritten.
Delivery Mechanism
All the implementations will be included into plastimatch.
References
- Demons algorithms for fluid and curvature registration. Cahill, N.D., Noble, J.A., Hawkes, D.J. ISBI 2009.
- A Demons Algorithm for Image Registration with Locally Adaptive Regularization. Cahill, N.D., Noble, J.A., Hawkes, D.J.. MICCAI 2009.
- High Accuracy Optical Flow Estimation Based on a Theory for Warping. Brox, T. et al., ECCV 2004